AGIs are what builds the simulations to revive theire frail biological creators..
AGI is far from inevitable
111–120 of 258 posts
Re: AGI is far from inevitable
#112Basically the linked article argues like this: > That’s because cognition, or the ability to observe, learn and gain new insight, is incredibly hard to replicate through AI on the scale that it occurs in the human brain. (no other more substantial arguments were given) I'm also very skeptical on seeing AGI soon, but LLMs do solve problems that people thought were extremely difficult to solve ten years ago.
> but LLMs do solve problems that people thought were extremely difficult to solve ten years ago
Agreed. I would have laughed you out of the room 5 years ago if you told me AI's would be writing code or carrying on coherent discussions on pretty complex topics in 2024.
As far as I'm concerned, all bets are off after the collective jaw drop that the entire software engineering industry did when we saw GPT4 released. We went from Google AI responses of "I'm sorry, I can't help with that." to ChatGPT writing pages of code that mostly works.
It turns out that the larger these models get, the more unexpected emergent capabilities they have, so I'm mostly in the camp of thinking AGI is just a matter of time and resources.
Re: AGI is far from inevitable
#113I'm in the other camp: I remember when we thought an AI capable of solving Go was astronomically impossible and yet here we are. This article reads just like the skeptic essays back then.
AGI is absolutely possible with current technology - even if it's only capable of running for a single user per-server-farm.
ASI on the other hand...
https://en.m.wikipedia.org/wiki/Integrated_information_theor...
Re: AGI is far from inevitable
#114Basically the linked article argues like this: > That’s because cognition, or the ability to observe, learn and gain new insight, is incredibly hard to replicate through AI on the scale that it occurs in the human brain. (no other more substantial arguments were given) I'm also very skeptical on seeing AGI soon, but LLMs do solve problems that people thought were extremely difficult to solve ten years ago.
> but LLMs do solve problems that people thought were extremely difficult to solve ten years ago Agreed. I would have laughed you out of the room 5 years ago if you told me AI's would be writing code or carrying on coherent discussions on pretty complex topics in 2024. As far as I'm concerned, all bets are off after the collective jaw drop that the entire software engineering industry did when we saw GPT4 released. W…
> It turns out that the larger these models get, the more unexpected emergent capabilities they have, so I'm mostly in the camp of thinking AGI is just a matter of time and resources.
AI research has a long history of people saying this. Whenever there is a new fundamental improvement, it looks like you can just keep getting better results by throwing more resources at it. However, eventually we end up reaching a point where throwing more resources at it stops meaningfully improving performance.
LLMs have an additional problem related to training data. We are already throwing all the data we can get our hands on at them. However, unlike most other AI systems we have developed, LLMs are actively polluting their data pool, so this intitial generation of LLMs are probably going to have the best data set of any that we ever develop. Of course, today's data will continue to be available, but will loose value as it ages.
Re: AGI is far from inevitable
#115Earlier quoted context omitted.
> How can you not understand the difference between "humans are not absolutely perfect or reliable at this task" and "LLMs by their very nature cannot perform this task"? This is a very good distillation of one side of it. What LLMs have taught us is a superficial grasp of language is good enough to reproduce a shocking proportion of what society has come to view as intelligent behaviors. i.e. it seems quite plausibl…
I think we already knew this though. Because the Turing test was passed by Eliza in the 1960's. PARRY was even better and not even a decade later. For some reason people still talk about Chess performance as if Deep Blue didn't demonstrate this. Hell, here's even Feynman talking about many of the same things we're discussing today, but this was in the 80's https://www.youtube.com/watch?v=EKWGGDXe5MA
Ten years ago I was explaining to halls of appalled academic administrators that AI would be replacing them before a robot succeeds in sorting out their socks.
Re: AGI is far from inevitable
#116Can't simulate the brain of an ant or a mouse.
Really don't expect ai to reach anything interesting.
If science doesn't understand intelligence, it means it cannot be made artificially.
Re: AGI is far from inevitable
#117This is a press release for a paper (a common thing university departments do) and we'd be better off with the paper itself as the story link: https://link.springer.com/article/10.1007/s42113-024-00217-5
The argument in the paper (that AGI through ML is intractable because the perfect-vs-chance problem is intractable) sounds similar to the uncomputability of Solomonoff induction (and AIXI, and the no free lunch theorem). Nobody thinks AGI is equivalent to Solomonoff induction. This paper is silly.
Re: AGI is far from inevitable
#118AGI is about as far away as it was two decades ago. Language models are merely a dent, and probably will be the precursor to a natural language interface to the thing.
AGI would seem to require consciousness or something that behaves in the same manner, and there does not seem to be anything along those lines currently or in the near future.
So far, everyone that has theorized that AGI will happen soon seems to be believe that with a sufficiently large amount of computing resources, "magic happens" and poof, we get AGI.
I've yet to hear anything more logical, but I'd love to.
Re: AGI is far from inevitable
#119Can't simulate the brain of an ant or a mouse. Really don't expect ai to reach anything interesting. If science doesn't understand intelligence, it means it cannot be made artificially.
>Can't simulate the brain of an ant or a mouse
We can't build a functional ornithopter, yet our aircraft fly like no bird ever possibly could.
You don't need the same processes to achieve the same result. Biological brains may not even be the best solution for intelligence; they are just a clunky approximation toward it that natural evolution has reached. See: all of human technology as an analogy.
Re: AGI is far from inevitable
#120I think "Janet" - the computer-person from The Good Place (especially after her reset) is what we are more likely to end up with.